Rotating machinery is an essential and crucial component of numerous mechanical systems in modern industries, transport vehicles, and in several other applications. Excessive vibrations on rotating equipment due to multiple faults may cause catastrophic failure in machines and lead to hazardous accidents. So, there is a need for perceiving the dynamic nature and identifying the faults for the safe, smooth and effective operation of machines. This paper proposes a novel trial misalignment approach to estimate the misalignment with a similar concept as the trial unbalance in the rotor balancing. Active magnetic bearing (AMB) misalignment with the rotor has been investigated with residual misalignment and additional trial misalignment cases. Additional trial misalignments are provided in addition to the unknown misalignments of the residual misalignment case. For the execution of this methodology, the dynamic model of a four-degree-of-freedom unbalanced and misaligned rigid rotor with two offset discs supported by two active magnetic bearings has been mathematically developed. The offset discs result in the gyroscopic effect at high rotor speeds. Equations of motion of the rotor-AMB system have been derived and solved to generate the time domain rotor displacement and controlling current responses at AMB positions. A fast Fourier transform technique has been utilized to convert the time domain responses into the frequency domain for estimation of unbalance eccentricities and phases together with force-displacement and force-current stiffnesses of misaligned AMBs as well as AMB's constant forces using the developed identification algorithm. Identified values of AMB's parameters for both residual and additional trial misalignment cases are evaluated to estimate the four unknown misalignments. Testing of the algorithm has also been carried out at multiple spin speeds against measurement signal noise in rotor responses and bias errors in rotor system parameters to check its effectiveness and robustness. The algorithm is found to be exhibiting excellent.

旋转机械是现代工业，运输车辆和其他几种应用中众多机械系统的重要组成部分。由于多个故障导致旋转设备上的过度振动可能会导致机器灾难性故障并导致危险事故。因此，为了机械的安全，平稳和有效的运行，需要感知动态特性并识别故障。本文提出了一种新颖的试验失准方法来估计失准，其概念与转子平衡中的试验失衡相似。主动磁轴承（AMB）与转子未对准的问题已通过剩余未对准和其他试验性未对准案例进行了研究。除了剩余未对齐情况的未知未对齐之外，还提供了其他试验未对齐。为了执行该方法，已经数学地开发了具有两个偏心盘且由两个主动磁轴承支撑的四自由度不平衡和未对准的刚性转子的动力学模型。偏置圆盘会在高转子转速下产生陀螺效应。已经推导并求解了转子AMB系统的运动方程，以生成时域转子位移并控制AMB位置处的电流响应。快速傅里叶变换技术已用于将时域响应转换为频域，以估计不平衡偏心率和相位以及未对准的AMB以及AMB'的力位移和力-电流刚度 使用已开发的识别算法来获得恒定的力。评估剩余和其他试验失准情况下AMB参数的识别值，以估计四个未知失准。还针对转子响应中的测量信号噪声和转子系统参数中的偏差误差，以多种自旋速度对算法进行了测试，以检查其有效性和鲁棒性。发现该算法表现出优异的性能。还针对转子响应中的测量信号噪声和转子系统参数中的偏差误差，以多种自旋速度对算法进行了测试，以检查其有效性和鲁棒性。发现该算法表现出优异的性能。还针对转子响应中的测量信号噪声和转子系统参数中的偏差误差，以多种自旋速度对算法进行了测试，以检查其有效性和鲁棒性。发现该算法表现出优异的性能。